Reappraisal of DEMs, Radar and optical datasets in lineaments extraction with emphasis on the spatial context

Lineaments mapping is an authentic issue for deciphering the tectonic setting, geological history, mineral prospecting, and other several applications. Consequently, study objective to examine various remote sensing datasets at wide spatial resolutions (10, 12.5, 15, 20, 30 m), recommend best in lineaments elicitation, usage scientific community. Toward this aim, nine including optical sensors (Landsat OLI, ASTER, Earth Observing-1 Advanced Land Imager, Sentinel 2A), radar data (Sentinel 1), digital elevation models (ALOS PALSAR, SRTM, NASA, ASTER V3), are tackled. In scope, we created entirely automatic lineament derivation environment through integration of edge detection line-linking algorithms. Results show that used less efficient than DEMs having same resolution. 1 more competent sources. ALOS PALSAR DEM (12.5m) eligible any utilized type even sentinel (10 m). Wholly, built from (e.g., DEM) proved their leverage extraction a limit can deviate well-known relationship between number extracted pixel size.